Název:	Line Clustering and Contour Extraction in the Context of 2D Building Plans
Autoři:	Pointner, Andreas Praschl, Christoph Krauss, Oliver Schuler, Andreas Helm, Emmanuel Zwettler, Gerald
Citace zdrojového dokumentu:	WSCG 2021: full papers proceedings: 29. International Conference in Central Europe on Computer Graphics, Visualization and Computer Vision, p. 11-20.
Datum vydání:	2021
Nakladatel:	Václav Skala - UNION Agency
Typ dokumentu:	conferenceObject konferenční příspěvek
URI:	http://hdl.handle.net/11025/45005
ISBN:	978-80-86943-34-3
ISSN:	2464-4617 2464–4625(CD/DVD)
Klíčová slova:	shlukování;extrakce obrysů;stavební plán;zpracování obrazu;strojové učení
Klíčová slova v dalším jazyce:	clustering;contour extraction;building plan;image processing;machine learning
Abstrakt v dalším jazyce:	For the purpose of analyzing a building according to its accessibility or structural resilience, printed 2D floorplans are not sufficient because of the missing link to semantic information. This paper tackles this issue andintroduces a concept for clustering classified lines of a floor plan and for creating semantically enriched contourelements based on different image processing, computer vision and machine learning algorithms. Based on ageneral line clustering approach, we introduce type specific methods forwalls,windows,doorsandstairs. Theresulting clusters are in turn used for a contour creation, which uses minimal rotated rectangles. Those rectanglesare transformed to polygons that are refined using post processing steps. The approach is evaluated via positivetesting using a pixel-based comparison of the process’s result. For this, automatically generated as well as realworld building plans are used. The final evaluation shows, that the concept reaches a confidence of >90% for door,stair and windows and only around 10% for stairs with the run-time linearly scaling with the size of the input.
Práva:	© Václav Skala - UNION Agency
Vyskytuje se v kolekcích:	WSCG 2021: Full Papers Proceedings

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